The goal of the project is to develop a large-area electronic x-ray detector for digital mammography in order to facilitate the early detection of breast cancer. Relative to existing methods, this system will allow greater image contrast at lower doses, more accurate imaging of low- contrast tissue, more efficient use of anti-scatter grids, and direct application of digital image-processing techniques. These improvements over existing methods will allow better resolution of features in radiographically dense breast tissue. The detector will be constructed from an array of four identical square "modules", each module consisting of an x-ray-to-light convertor, a fiberoptic taper, and a CCD. The four modules will be butted together to form a large area, with the outputs from each of the modules will be combined to form a single image. Hardware and software methods will be developed to recover the small sections (0.1% of the total image area) obscured by the inter-module gaps. This detector will have excellent spatial resolution, low noise, high sensitivity and high dynamic range. The basic technology for this detector has already been developed by our group for x-ray crystallography. This technology will be transferred to mammographic imaging and augmented with new methods required for digital mammography. The project consists of the following components, each of which is critical to its successful completion: (1) development of design models which accurately predict detector performance; (2),development of hardware methods such as optimized phosphor screens, CCD-to-fiberoptic bonding, and methods for recovery of the data at inter-module gaps; (3) development of software for data collection, calibration, correction, recovery and visualization; (4) stepwise construction of the modular detector; (5) testing and evaluation of detector performance by measures such as the response linearity, dynamic range, modulation-transfer function and detective quantum efficiency; and (6) evaluation of detector performance for mammography by imaging phantoms and specimens. Performance will be measured in parallel with development, in order to work out an optimal detector design. Clinical evaluation of this system will be performed in a program to be initiated during the second year of this project. At the completion of the funding period, the hardware and software components of the detector will have been developed, tested, and integrated, and the detector will be ready for commercialization.